Abstract The burden of cognitive impairment and Alzheimer disease (AD) is increasing rapidly with the aging of the US population. Accordingly, it is critical to identify molecular signatures of the long pre-symptomatic phase of AD to identify and target its clinically silent phase. New criteria of preclinical AD use structural and molecular imaging (MRI and PET) and cerebrospinal fluid (CSF) assays, which are expensive, invasive and not scalable for population-based screening. Hence, there is a quest for blood biomarkers of pre-symptomatic stages, mild cognitive impairment (MCI), and dementia that could (i) elucidate the biology of `normal' brain aging, AD and AD-related dementias (ADRD), (ii) improve risk prediction of AD, and iii) permit risk stratification and subject selection for enrollment in targeted clinical trials of early preclinical disease. AD is an archetypal proteinopathy characterized by protein misfolding and formation of neurotoxic protein aggregates. Damaged cerebral proteins leak into the CSF and can enter the blood. Therefore, ultra-sensitive proteomic profiling has been used to identify blood biomarkers of pre-dementia and AD. Yet, initial studies have been small, limited by suboptimal designs, and an absence of analytical validation and replication. We will characterize the plasma proteome (1310 SomaScan proteins) at two critical time points (mid-life and older age) in 1874 middle-aged-to-elderly individuals in the Framingham Offspring Study (FOS) spanning the spectrum of normal and abnormal cognition. Participants have serial neurocognitive and brain imaging data (including PET scans in a subset) and are under surveillance for AD. We hypothesize that the plasma proteome changes with the aging and with early changes in cognition. We posit that longitudinal patterns of blood biomarkers can distinguish normal aging from presence of comorbidities, pre-dementia, MCI and AD. Our specific aims are: Aim 1. Characterize the plasma proteome in 1874 elderly FOS participants at their tenth exam (2019-2021), and relate the proteome cross-sectionally to risk factors, lifestyle and medications; function of body systems and comorbidities; and structural/cognitive endophenotypes of AD. Aim 2. Evaluate longitudinal changes in plasma proteins with aging over a 25-yr follow-up period (between the 5th and 10th exams; using extant protein data at former), and relate protein changes to longitudinal trajectories of neurocognitive and brain imaging measures. Aim 3. Relate the plasma proteome at exam 10 (and changes between exams) to the incidence of cognitive decline, stroke and AD prospectively. Aim 4. Relate the top proteomic findings in Aims 1-3 to brain amyloid and tau on PET scans in a subset. We will validate our findings with mass spectrometry, and replicate them in independent cohorts. Our multidisciplinary team will identify novel longitudinal proteomic signatures of AD and ADRD; construct biological protein networks associated with AD that may be targeted in clinical trials for preventing cognitive decline and AD in middle age and beyond.